This paper proposes a tree kernel with contextsensitive structured parse tree information for relation extraction. It resolves two critical problems in previous tree kernels for r...
Guodong Zhou, Min Zhang, Dong-Hong Ji, Qiaoming Zh...
Kernel coupling refers to the effect that kernel i has on kernel j in relation to running each kernel in isolation. The two kernels can correspond to adjacent kernels or a chain ...
Jonathan Geisler, Valerie E. Taylor, Xingfu Wu, Ri...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...